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ICLR2025顶会

Youku Dense Caption: A Large-scale Chinese Video Dense Caption Dataset and Benchmarks

Zixuan Xiong, Guangwei Xu, Wenkai Zhang, Yuan Miao, Xuan Wu, LinHai, Ruijie Guo, Hai-Tao Zheng

出版方
2025年份

摘要

With the explosive growth of video content, video captions have emerged as a crucial tool for video comprehension, significantly enhancing the ability to understand and retrieve information from videos. However, most publicly available dense video captioning datasets are in English, resulting in a scarcity of largescale and high-quality Chinese dense video captioning datasets. To address this gap within the Chinese community and to promote the advancement of Chinese multi-modal models, we develop the first, large-scale, and high-quality Chinese dense video captioning dataset, named Youku Dense Caption. This dataset is sourced from Youku, a prominent Chinese video-sharing website. Youku Dense Caption includes 31,466 complete short videos annotated by 311,921 Chinese captions. To the best of our knowledge, it is currently the largest publicly available dataset for fine-grained Chinese video descriptions. Additionally, we establish several benchmarks for Chinese video-language tasks based on the Youku Dense Caption, including retrieval, grounding, and generation tasks. Extensive experiments and evaluations are conducted on existing state-of-the-art multi-modal models, demonstrating the dataset's utility and the potential for further research. The dataset is publicly available at https://github.com/OpenSearch-AI/Youku-Dense-Caption.

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